class_docstr: CelebA-HQ dataset, downsampled as 128x128.
docstr: Get filepattern for data files for mode.
  
  Args:
    data_dir: str, data directory.
    mode: DatasetSplit
    shard: int, if provided, will only read data from the specified shard.
  
  Returns:
    filepattern str
docstr_tok: ["Get","filepattern","for","data","files","for","mode",".","Args",":","data_dir",":","str",",","data","directory",".","mode",":","DatasetSplit","shard",":","int",",","if","provided",",","will","only","read","data","from","the","specified","shard",".","Returns",":","filepattern","str"]
code: def filepattern(self, data_dir, mode, shard=None):
      """Get filepattern for data files for mode.
  
      Args:
        data_dir: str, data directory.
        mode: DatasetSplit
        shard: int, if provided, will only read data from the specified shard.
  
      Returns:
        filepattern str
      """
      path = os.path.join(data_dir, self.dataset_filename())
      if shard is not None:
          shard_str = "%05d" % shard
      elif mode == problem.DatasetSplit.TRAIN:
          # Use the first 90 shards.
          shard_str = "000[0-8]"
      else:
          assert mode in [
              problem.DatasetSplit.EVAL,
              tf_estimator.ModeKeys.PREDICT,
              problem.DatasetSplit.TEST,
          ]
          # Use the last 10 shards.
          shard_str = "0009"
  
      return "%s-%s*" % (path, shard_str)
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import os
  from tensor2tensor.data_generators import image_utils
  from tensor2tensor.data_generators import problem
  from tensor2tensor.layers import modalities
  from tensor2tensor.utils import metrics
  from tensor2tensor.utils import registry
  import tensorflow.compat.v1
  from tensorflow.compat.v1 import estimator
label_desc: Use image node_id 3 for calling the ImageCelebahq128 obj's underlying member method code with example usage: obj.filepattern(data_dir, mode, shard) and returns: unknown